The 3rd Generation Partnership Project (3GPP) is responsible for the standardization of UMTS (Universal Mobile Telecommunication Service) system and LTE (Long Term Evolution). LTE is a technology for realizing high-speed packet-based communication that can reach high data rates both in the downlink (DL) and in the uplink (UL), which is thought as a next generation mobile communication system of the UMTS system. The 3GPP work on LTE is also referred to as E-UTRAN (Evolved Universal Terrestrial Access Network). The first release of LTE, referred to as release-8 (Rel-8) can provide peak rates of 300 Mbps, a radio-network delay of e.g. 5 ms or less, a significant increase in spectrum efficiency and a network architecture designed to simplify network operation, reduce cost, etc. In order to support high data rates, LTE allows for a system bandwidth of up to 20 MHz. LTE is also able to operate in different frequency bands and can operate in at least FDD (Frequency Division Duplex) and TDD (Time Division Duplex). The modulation technique or the transmission scheme used in LTE is known as OFDM (Orthogonal Frequency Division Multiplexing).
The next generation mobile communications system e.g. IMT-Advanced (International Mobile Telecommunications) and/or LTE-Advanced (LTE-A), which is an evolution of LTE, and supports bandwidths of up to 100 MHz is being discussed. LTE-A can be viewed as a future release of the LTE standard and since it is an evolution of LTE, backward compatibility is important because LTE-A could be deployed in spectrum that is already occupied by LTE. In both LTE and LTE-A radio base stations known as eNBs or eNodeBs—where e stands for evolved-, multiple antennas with precoding/beamforming technology can be adopted in order to provide high data rates to user equipments. Thus, LTE and LTE-A are examples of MIMO (Multiple-Input, Multiple-Output) radio systems. Another example of a MIMO based system is WiMAX (Worldwide Interoperability for Microwave Access) system.
In a cellular telecommunication system which typically comprises, as illustrated in FIG. 1, a core network 1, a radio access network 2, User Equipment (UEs) 4 and 5 and at least one radio base station 3, multiple transmit antennas can be used for achieving high data rates in various ways. A multiple-input-multiple-output (MIMO) channel is formed if also the receiver has multiple antennas. One application in such a setup is to strive for high peak rates to a single user. By transmitting on several layers which means that the information is transmitted on several bit streams the information is spread in the spatial domain, substantial improvement in data rate can be achieved under favourable channel conditions.
The number of simultaneously transmitted layers depends on the properties of the MIMO channel. Because of for example fading, usually the MIMO channel does not support more than one layer transmission to a single UE. This limits the data rate and means that spatial multiplexing gain is not possible. To reach higher system capacity it would be beneficial to transmit only a limited number of layers to a single user and instead schedule several users on the same physical resource (e.g. time-frequency-code tile) and use the spatial domain (layers) to separate the users. In essence, then layers belonging to different users are transmitted on the same physical resource. Even if the channel to a particular user is such that it does not support multiple layers, which means that it is not possible to transmit multiple layers to that particular user, spatial multiplexing gain on a system level can be achieved as long as the user can efficiently suppress the layers transmitted to the other users. This technique is often referred to as multi-user MIMO (MU-MIMO) and is especially attractive in high load scenarios with many active users.
FIG. 2 shows an example of a base station 30, with multiple transmit antennas 33, transmitting in MU-MIMO mode to multiple UEs 40, 50 and 60. As shown in FIG. 2 different layer 44, 55 and 66 is transmitted to each UE 40, 50 and 60. As also illustrated in FIG. 2 each UE is also transmitting to the base station 30 using different layers.
Multi-user MIMO (MU-MIMO) is a set of advanced MIMO technologies that exploit the availability of multiple independent radio terminals in order to enhance the communication capabilities of each individual terminal. MU-MIMO can be seen as the extended concept of Space-Division Multiple Access (SDMA), which allows eNodeB to transmit (or receive) signal to (or from) multiple users in the same frequency band simultaneously.
In LTE, the MU-MIMO scheme is supported. More specifically,                In LTE Rel-8, MU-MIMO is supported in both uplink and downlink as specified in 3GPP technical specification TS 36.211 version 9.0.0. In the uplink, the eNodeB can always schedule more than one UE to transmit in the same time-frequency resource. In the downlink, if a UE is configured to be in the MU-MIMO transmission mode, only rank-1 transmission can be scheduled to the UE. The eNodeB can schedule multiple UEs in the same time-frequency resource using different rank-1 precoding matrices.        In LTE Ret-9, a more advanced MU-MIMO scheme is specified, where up to two UEs can be scheduled in two different orthogonal demodulation reference signals (DM-RS) [1]. At least, channel estimation for each UE has less impact by UE pairing algorithm.        In LTE-A, i.e. Rel-10, MU-MIMO is being further discussed in 3GPP technical specification TS 36.814 version 1.5.0, nevertheless Rel-9 MU-MIMO functionality is taken as a baseline.        
Theoretically, the performance of wireless communication systems can be improved by having multiple antennas at the transmitter side and the receiver side. In practice, the channels between different antennas are often correlated and therefore the potential multi-antenna gains may not always be obtainable. This is called spatial correlation as it can be interpreted as a correlation between a signal's spatial direction and the average received signal gain.
High spatial correlation is when channel fading coefficients are statistically close or correlated.
Low spatial correlation is when channel fading coefficients are statistically independent or un-correlated.
The MIMO performance, and particularly the MU-MIMO performance, then relies on good UE pairing and/or co-scheduling at the radio base station or eNodeB side. Essentially, only the UEs with good spatial separation or low spatial correlation may or should be co-scheduled in the same time-frequency resource.
So, in order to guarantee MIMO performance, and particularly MU-MIMO performance, it is important for an eNodeB base station to obtain channel state information (CSI), including one or more of Channel Quality Indication, (CQI), Precoder Matrix Indication (PMI), ACK/NACK information and Rank Indication (RI), from each UE to judge whether or not they can be co-scheduled. For instance, in FDD, PMI-like feedback can be used while in TDD, DL/UL channel reciprocity can be exploited. Good MU-MIMO pairing performance for example relies on interference suppression between co-scheduled UEs. Spatial correlation is measured and or calculated to judge interference leakage between UEs. The larger the spatial correlation, the more serious the interference leakage is.
More specifically, a radio base station may obtain CSI information (i.e. channel fading coefficients) from each UE via e.g. PMI feedback from codebooks when in FDD/TDD mode or by performing channel estimation on uplink sounding reference signals, SRS, to exploit DL/UL reciprocity when in TDD mode.
Conventional UE pairing algorithms are usually based on the measurement of spatial correlation by using obtained CSI from each UE. However, such a measurement is not enough to guarantee low interference between paired UEs, due to mismatch factors on CSI accuracy. More specifically, such factors include but are not limited to feedback delay, channel estimation or prediction errors, and quantized feedback. Factors that influence the accuracy of channel state information, CSI, are among other things dependent on that:                Interference information cannot be truly reflected at the radio base station or eNB side. Typically in LTE Rel-8, The UE generates the PMI/CQI feedback without any knowledge about other simultaneously scheduled UEs. Hence, there could be mismatch between the UE's CQI report and the actual CQI experienced due to lack of knowledge of interference caused by another UE scheduled simultaneously. Even in TDD case, DL/UL interference is not reciprocal, which determines CSI accuracy will be influenced. Other factors also include estimation errors, prediction errors and quantization errors.        Mobility impact can not be really captured by eNB. There always exists scheduling duration between CSI feedback/measurements and actual downlink or uplink scheduling. Over time, channels could vary with time. The higher the UE mobility is, the faster the channel varies. The mismatch of CSI accuracy between feedback and scheduling could impact the scheduling strategy relying on spatial correlation.        
The UEs co-scheduled in downlink or uplink could have different feedback time, which further introduce CSI mismatch between UEs. FIG. 3 shows one such example of CSI mismatch between two UEs due to different feedback times for both TDD and FDD, where PMI feedback is used for FDD and channel reciprocity feedback is used for TDD.